Just a decade ago, large-scale flows of information such as news feeds were owned, monitored, and filtered by organizations specializing in the provision of news. The Web has brought the challenges and opportunities of managing and absorbing news feeds to all interested users. Identifying “important” information has been an essential aspect of studies on Web search and text summarization. Search methods focus on identifying a set of documents that maximally satisfies a user's acute information needs. Summarization strives at compressing large quantities of text into a more concise formulation. In the absence of automated methods for identifying the deep semantics associated with text, prior work in summarization has typically operated at the level of complete sentences, weaving together the most representative sentences to create a document summary. Research on search and summarization has generally overlooked the dynamics of informational content arriving continuously over time.